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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 04 Nov 2009 13:57:34 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/04/t1257368364ra5n0wjsuxu6p0t.htm/, Retrieved Mon, 29 Apr 2024 13:26:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53847, Retrieved Mon, 29 Apr 2024 13:26:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws5bel36mldg
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS5: Bivariate ED...] [2009-11-04 20:57:34] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
- RMPD    [Kendall tau Rank Correlation] [WS 5: Kendall ran...] [2009-11-04 21:11:24] [7c2a5b25a196bd646844b8f5223c9b3e]
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Dataseries X:
-2,225348423
2,257563984
1,740476391
3,706301205
7,959396904
-1,810786388
-1,764228405
-1,270419804
4,26994678
0,614671842
1,706301205
4,797930568
6,99357209
2,027747276
-1,627527662
-3,076264883
-0,444268937
1,268460179
1,670639417
3,325914355
4,085201453
1,936117913
-4,638423857
-9,15551145
-2,385328158
-1,30459499
-5,936590936
-15,08567448
-11,20058283
-4,660216246
-1,464574724
-3,7751246
-3,20058283
-10,00494131
-3,315491184
-1,004941308
3,454692108
3,201596409
6,833592356
4,627054639
6,052512869
1,07579186
3,822696161
2,086688055
-1,740949414
-0,362049167
2,580496656
5,901942727
4,867767541
-0,017324105
3,810313364
4,051026267
0,672126019
-0,293698795
1,855384745
-1,43188614
-3,444268937
3,945527506
3,541861665
7,506199877
0,816749754
1,000008479
-1,770174813
-9,549075061
-2,783250246
-4,981417326
-1,341050742
0,916057116
-3,913759591
Dataseries Y:
453.76
567.15
-1861.46
-7454.68
-11242.01
-11289.29
11715.62
19336.27
20729.84
17062.92
10369.32
11258.72
10721.21
10375.43
8202.51
2834.34
-371.69
-2429.58
19711.67
23745.59
25554.61
21797.03
15266.24
16605.63
14210.92
14714.05
11338.08
10074.50
9246.14
6347.71
25088.21
25798.35
27194.14
13649.64
4755.79
1004.64
4035.07
-1054.60
-10228.63
-11699.39
-18817.18
-29199.23
-6246.90
-4201.96
-10585.42
-15033.13
-22236.31
-18963.19
-17206.41
-20744.05
-28649.59
-29339.61
-40442.91
-39478.68
-18740.10
-18252.00
-20542.69
-23465.13
-23725.81
-15453.46
-6685.61
-3334.80
1292.91
2637.62
-3574.61
1701.23
22560.80
26551.57
24040.85




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53847&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53847&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53847&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c-0.000434911299066892
b-1268.51819522574

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.000434911299066892 \tabularnewline
b & -1268.51819522574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53847&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.000434911299066892[/C][/ROW]
[ROW][C]b[/C][C]-1268.51819522574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53847&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53847&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c-0.000434911299066892
b-1268.51819522574







Descriptive Statistics about e[t]
# observations69
minimum-39851.2418304621
Q1-11031.5578692010
median-952.588524109518
mean2.23306075724026e-13
Q312533.7945599894
maximum30736.7628092044

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -39851.2418304621 \tabularnewline
Q1 & -11031.5578692010 \tabularnewline
median & -952.588524109518 \tabularnewline
mean & 2.23306075724026e-13 \tabularnewline
Q3 & 12533.7945599894 \tabularnewline
maximum & 30736.7628092044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53847&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]69[/C][/ROW]
[ROW][C]minimum[/C][C]-39851.2418304621[/C][/ROW]
[ROW][C]Q1[/C][C]-11031.5578692010[/C][/ROW]
[ROW][C]median[/C][C]-952.588524109518[/C][/ROW]
[ROW][C]mean[/C][C]2.23306075724026e-13[/C][/ROW]
[ROW][C]Q3[/C][C]12533.7945599894[/C][/ROW]
[ROW][C]maximum[/C][C]30736.7628092044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53847&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53847&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations69
minimum-39851.2418304621
Q1-11031.5578692010
median-952.588524109518
mean2.23306075724026e-13
Q312533.7945599894
maximum30736.7628092044



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')